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Knowledge in microbiology is reaching an extreme level of diversification and complexity, which paradoxically results in a strong reduction in the intelligibility of microbial life. In our days, the "score of life" metaphor is more accurate to express the complexity of living systems than the classic "book of life." Music and life can be represented at lower hierarchical levels by music scores and genomic sequences, and such representations have a generational influence in the reproduction of music and life. If music can be considered as a representation of life, such representation remains as unthinkable as life itself. The analysis of scores and genomic sequences might provide mechanistic, phylogenetic, and evolutionary insights into music and life, but not about their real dynamics and nature, which is still maintained unthinkable, as was proposed by Wittgenstein. As complex systems, life or music is composed by thinkable and only showable parts, and a strategy of half-thinking, half-seeing is needed to expand knowledge. Complex models for complex systems, based on experiences on trans-hierarchical integrations, should be developed in order to provide a mixture of legibility and imageability of biological processes, which should lead to higher levels of intelligibility of microbial life. ; Work in the laboratory of Fernando Baquero is funded by research grants from the European Commission (PAR-241476-FP-HEALTH-2009 and EvoTAR-FP-HEALTH-F3-2011-282004), the CIBERESP Research Network in Epidemiology and Public Health (CB06/02/0053), and the Regional Government of Madrid (PROMPT-CM-CM S2010/BMD-2414), and Andrés Moya by the grants SAF2009-13032-C02-01 of Ministry of Economy and Innovation and Prometeo /2009/092 of the Regional Government of Valencia, Spain. ; Peer reviewed ; Peer Reviewed

Antibiotics have natural functions, mostly involving cell-to-cell signaling networks. The anthropogenic production of antibiotics, and its release in the microbiosphere results in a disturbance of these networks, antibiotic resistance tending to preserve its integrity. The cost of such adaptation is the emergence and dissemination of antibiotic resistance genes, and of all genetic and cellular vehicles in which these genes are located. Selection of the combinations of the different evolutionary units (genes, integrons, transposons, plasmids, cells, communities and microbiomes, hosts) is highly asymmetrical. Each unit of selection is a self-interested entity, exploiting the higher hierarchical unit for its own benefit, but in doing so the higher hierarchical unit might acquire critical traits for its spread because of the exploitation of the lower hierarchical unit. This interactive trade-off shapes the population biology of antibiotic resistance, a composed-complex array of the independent "population biologies." Antibiotics modify the abundance and the interactive field of each of these units. Antibiotics increase the number and evolvability of "clinical" antibiotic resistance genes, but probably also many other genes with different primary functions but with a resistance phenotype present in the environmental resistome. Antibiotics influence the abundance, modularity, and spread of integrons, transposons, and plasmids, mostly acting on structures present before the antibiotic era. Antibiotics enrich particular bacterial lineages and clones and contribute to local clonalization processes. Antibiotics amplify particular genetic exchange communities sharing antibiotic resistance genes and platforms within microbiomes. In particular human or animal hosts, the microbiomic composition might facilitate the interactions between evolutionary units involved in antibiotic resistance. The understanding of antibiotic resistance implies expanding our knowledge on multi-level population biology of bacteria. ; The authors' work was sponsored by grants from the European Union (PAR-241476 and EvoTAR-282004), the Instituto de Salud Carlos III – Ministry of Economy and Competitiveness of Spain (FIS-PS09-02381; FIS-PI10-02588, PI12-01581), and the Regional Government of Madrid in Spain (PROMPT- S2010/BMD2414). The authors are also grateful to the Spanish Network for the Study of Plasmids and Extrachromosomal Elements (REDEEX) for encouraging and funding cooperation among Spanish microbiologists working on the biology of mobile genetic elements (grant BFU 2012-0079-E/BMC; Spanish Ministry of Science and Innovation). ; Peer reviewed ; Peer Reviewed

Minireview.-- Free via Open Access. ; In recent years, the explosive spread of antibiotic resistance determinants among pathogenic, commensal, and environmental bacteria has reached a global dimension. Classical measures trying to contain or slow locally the progress of antibiotic resistance in patients on the basis of better antibiotic prescribing policies have clearly become insufficient at the global level. Urgent measures are needed to directly confront the processes influencing antibiotic resistance pollution in the microbiosphere. Recent interdisciplinary research indicates that new eco-evo drugs and strategies, which take ecology and evolution into account, have a promising role in resistance prevention, decontamination, and the eventual restoration of antibiotic susceptibility. This minireview summarizes what is known and what should be further investigated to find drugs and strategies aiming to counteract the ¿four P¿s,¿ penetration, promiscuity, plasticity, and persistence of rapidly spreading bacterial clones, mobile genetic elements, or resistance genes. The term ¿drug¿ is used in this eco-evo perspective as a tool to fight resistance that is able to prevent, cure, or decrease potential damage caused by antibiotic resistance, not necessarily only at the individual level (the patient) but also at the ecological and evolutionary levels. This view offers a wealth of research opportunities for science and technology and also represents a large adaptive challenge for regulatory agencies and public health officers. Eco-evo drugs and interventions constitute a new avenue for research that might influence not only antibiotic resistance but the maintenance of a healthy interaction between humans and microbial systems in a rapidly changing biosphere. ; Work in the laboratories of F.B. and T.M.C. is funded by research grants from the European Commission (LSHM-2006-037410, LSHMCT-2008-223031, KBBE-2008-2B-227258, and PAR-241476-FPHEALTH 2009), the Fondo de Investigaciones Sanitarias, Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation (grants PS09/02381 and PI10/02588; the CIBERESP research network in Epidemiology and Public Health [CB06/02/0053]), and the Regional Government of Madrid (DeRemicrobiana Network [CAM.S-SAL-0246- 2006]). Work in the laboratory of F.D.L.C. is supported by research grants from the Spanish Ministry of Education (BFU2008-00995/ BMC), the Fondo de Investigaciones Sanitarias, Instituto de Salud Carlos III, Spanish Ministry of Science and Innovation (REIPI network [RD06/0008/1012]) and the European Commission (LSHM-CT- 2005_019023). We are also grateful to the Spanish Network for the Study of Plasmids and Extrachromosomal Elements (REDEEX) for encouraging and funding cooperation among Spanish microbiologists working on the biology of mobile genetic elements (Spanish Ministry of Science and Innovation, reference number BFU 2008-0079-E/ BMC). ; Peer Reviewed

To address the public health problem of antibiotic resistance, the European Union (EU) founded the European Antimicrobial Resistance Surveillance System. A network of 40 hospitals that serve approximately 30% of the Spanish population (about 12 million) participated. Each laboratory reported data on antimicrobial susceptibility testing using standard laboratory procedures that were evaluated by an external quality control program. The antibiotic consumption data were obtained from the National Health System. We compared the antibiotic susceptibility of Spanish isolates of invasive Streptococcus pneumoniae (2001 to 2003) with antibiotic consumption. Invasive S. pneumoniae was isolated from 1,968 patients, 20% of whom were children at or below the age of 14 years. Of non-penicillin-susceptible strains (35.6%; 95% confidence interval, 34 to 37.2), 26.4% were considered intermediate and 9.2% were considered resistant. Between 2001 and 2003, penicillin resistance decreased from 39.5 to 33% overall and from 60.4 to 41.2% in children at or below the age of 14 years (P = 0.002). Resistance to erythromycin was at 26.6%, and coresistance with penicillin was at 19.1%. Of total isolates, the ciprofloxacin MIC was >2 μg/ml for 2.1%, with numbers increasing from 0.4% (2001) to 3.9% (2003). Total antibiotic use decreased from 21.66 to 19.71 defined daily doses/1,000 inhabitants/day between 1998 and 2002. While consumption of broad-spectrum penicillins, cephalosporins, and erythromycin declined, use of amoxicillin-clavulanate and quinolones increased by 17.5 and 27%, respectively. The frequency of antibiotic resistance in invasive S. pneumoniae in Spain was among the highest in the EU. However, a significant decrease in penicillin resistance was observed in children. This decrease coincided with the introduction of a heptavalent conjugate pneumoccocal vaccine (June 2001) and with a global reduction in antibiotic consumption levels.

Ampicillin resistance has greatly contributed to the recent dramatic increase of a cluster of human adapted Enterococcus faecium lineages (ST17, ST18, and ST78) in hospital-based infections. Changes in the chromosomal pbp5 gene have been associated with different levels of ampicillin susceptibility, leading to protein variants (designated as PBP5 C-types to keep the nomenclature used in previous works) with diverse degrees of reduction in penicillin affinity. Our goal was to use a comparative genomics approach to evaluate the relationship between the diversity of PBP5 among E. faecium isolates of different phylogenomic groups as well as to assess the pbp5 transferability among isolates of disparate clonal lineages. The analyses of 78 selected E. faecium strains as well as published E. faecium genomes, suggested that the diversity of pbp5 mirrors the phylogenomic diversification of E. faecium. The presence of identical PBP5 C-types as well as similar pbp5 genetic environments in different E. faecium lineages and clones from quite different geographical and environmental origin was also documented and would indicate their horizontal gene transfer among E. faecium populations. This was supported by experimental assays showing transfer of large (≈180–280 kb) chromosomal genetic platforms containing pbp5 alleles, ponA (transglycosilase) and other metabolic and adaptive features, from E. faecium donor isolates to suitable E. faecium recipient strains. Mutation profile analysis of PBP5 from available genomes and strains from this study suggests that the spread of PBP5 C-types might have occurred even in the absence of a significant ampicillin resistance phenotype. In summary, genetic platforms containing pbp5 sequences were stably maintained in particular E. faecium lineages, but were also able to be transferred among E. faecium clones of different origins, emphasizing the growing risk of further spread of ampicillin resistance in this nosocomial pathogen. ; This work was supported by Fundação para a Ciência e a Tecnologia (FCT)/Ministério da Educacão e Ciência (MEC) through national funds and co-financed by Fundo Europeu de Desenvolvimento Regional (FEDER) under the Partnership Agreement PT2020 with the reference UID/ MULTI/04378/2013–POCI/01/0145/FERDER/007728 to CN and LP, Instituto de Salud Carlos III (Plan Estatal de I+D+i 2013-2016), Grant PI12-01581 and PI15-01307 to TMC and CIBERESP (CB06/02/0053) to FB, European Commission, Seventh Framework Program (EVOTARFP7-HEALTH-282004) to TMC and FB and the Regional Government of Madrid in Spain (PROMPT- S2010/BMD2414) to FB and TMC. ; Peer reviewed ; Peer Reviewed

Enterococci are Gram-positive bacteria that are found in plants, soil and as commensals of the gastrointestinal tract of humans, mammals, and insects. Despite their commensal nature, they have also become globally important nosocomial pathogens. Within the genus Enterococcus, Enterococcus faecium, and Enterococcus faecalis are clinically most relevant. In this review, we will discuss how E. faecium and E. faecalis have evolved to become a globally disseminated nosocomial pathogen. E. faecium has a defined sub-population that is associated with hospitalized patients and is rarely encountered in community settings. These hospital-associated clones are characterized by the acquisition of adaptive genetic elements, including genes involved in metabolism, biofilm formation, and antibiotic resistance. In contrast to E. faecium, clones of E. faecalis isolated from hospitalized patients, including strains causing clinical infections, are not exclusively found in hospitals but are also present in healthy individuals and animals. This observation suggests that the division between commensals and hospital-adapted lineages is less clear for E. faecalis than for E. faecium. In addition, genes that are reported to be associated with virulence of E. faecalis are often not unique to clinical isolates, but are also found in strains that originate from commensal niches. As a reflection of more ancient association of E. faecalis with different hosts, these determinants Thus, they may not represent genuine virulence genes but may act as host-adaptive functions that are useful in a variety of intestinal environments. The scope of the review is to summarize recent trends in the emergence of antibiotic resistance and explore recent developments in the molecular epidemiology, population structure and mechanisms of adaptation of E. faecium and E. faecalis. ; WS is funded through a NWO-Vidi grant (917.13.357). TC and FB are supported by grants PI12-01581 and PI15-01307 from the ISCIII-Ministry of Economy and Competitiveness of Spain (to TC), S2010/BMD2414 from the Regional Government of Madrid (to FB) and the CIBERESP Network for Biomedical Research in Epidemiology and Public Health (Instituto Carlos III, Spanish Ministry of Science and Innovation, reference number CB06/02/0053). ; Peer reviewed ; Peer Reviewed

Epidemics caused by microbial organisms are part of the natural phenomena of increasing biological complexity. The heterogeneity and constant variability of hosts, in terms of age, immunological status, family structure, lifestyle, work activities, social and leisure habits, daily division of time, and other demographic characteristics make it extremely difficult to predict the evolution of epidemics. Such prediction is, however, critical for implementing intervention measures in due time and with appropriate intensity. General conclusions should be precluded, given that local parameters dominate the flow of local epidemics. Membrane computing models allows us to reproduce the objects (viruses, hosts) and their interactions (stochastic but also with defined probabilities) with an unprecedented level of detail. Our LOIMOS model helps reproduce the demographics and social aspects of a hypothetical town of 10,320 inhabitants in an average European country where COVID-19 is imported from the outside. The above-mentioned characteristics of hosts and their lifestyle are minutely considered. The dynamics of the epidemics are reproduced and include the effects on viral transmission of innate and acquired immunity at various ages. The model predicts the consequences of delaying the adoption of non-pharmaceutical interventions (between 15 and 45 days after the first reported cases) and the effect of those interventions on infection and mortality rates (reducing transmission by 20%, 50%, and 80%) in immunological response groups. The lockdown for the elderly population as a single intervention appears to be effective. This modelling exercise exemplifies the application of membrane computing for designing appropriate interventions in epidemic situations. ; MC and FB were sponsored by the Projects COV20_00067 of the Program SARS-COV-2 and COVID-19 infection of the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación of Spain, CB06/02/0053 of the Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), and the Regional Government of Madrid (InGeMICS-B2017/BMD-3691). For JCG, this study was partially founded by the Autonomous Community of Madrid, Spain (COVID-19 Grant, 2020) and the Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain. For AM, this study was supported by grants from the Spanish Ministry of Science and Innovation (PID2019-105969GB-I00), the government of Valencia (project Prometeo/2018/A/133) and cofinanced by the European Regional Development Fund (ERDF). ; No

Epidemics caused by microbial organisms are part of the natural phenomena of increasing biological complexity. The heterogeneity and constant variability of hosts, in terms of age, immunological status, family structure, lifestyle, work activities, social and leisure habits, daily division of time and other demographic characteristics make it extremely difficult to predict the evolution of epidemics. Such prediction is, however, critical for implementing intervention measures in due time and with appropriate intensity. General conclusions should be precluded, given that local parameters dominate the flow of local epidemics. Membrane computing models allows us to reproduce the objects (viruses and hosts) and their interactions (stochastic but also with defined probabilities) with an unprecedented level of detail. Our LOIMOS model helps reproduce the demographics and social aspects of a hypothetical town of 10 320 inhabitants in an average European country where COVID-19 is imported from the outside. The above-mentioned characteristics of hosts and their lifestyle are minutely considered. For the data in the Hospital and the ICU we took advantage of the observations at the Nursery Intensive Care Unit of the Consortium University General Hospital, Valencia, Spain (included as author). The dynamics of the epidemics are reproduced and include the effects on viral transmission of innate and acquired immunity at various ages. The model predicts the consequences of delaying the adoption of non-pharmaceutical interventions (between 15 and 45 days after the first reported cases) and the effect of those interventions on infection and mortality rates (reducing transmission by 20, 50 and 80%) in immunological response groups. The lockdown for the elderly population as a single intervention appears to be effective. This modeling exercise exemplifies the application of membrane computing for designing appropriate multilateral interventions in epidemic situations. ; MC and FB were sponsored by the Projects COV20_00067 of the Program SARS-COV-2 and COVID-19 infection of the Instituto de Salud Carlos III, Ministerio de Ciencia e Innovación of Spain, CB06/02/0053 of the Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), and the Regional Government of Madrid (InGeMICS-B2017/BMD-3691). For JCG, this study was partially founded by the Autonomous Community of Madrid, Spain (COVID-19 Grant, 2020) and the Ramón y Cajal Institute for Health Research (IRYCIS), Madrid, Spain. For AM, this study was supported by grants from the Spanish Ministry of Science and Innovation (PID2019-105969GB-I00), the government of Valencia (project Prometeo/2018/A/133) and co-financed by the European Regional Development Fund (ERDF). ; Peer reviewed

Membrane computing is a bio-inspired computing paradigm whose devices are the so-called membrane systems or P systems. The P system designed in this work reproduces complex biological landscapes in the computer world. It uses nested "membrane-surrounded entities" able to divide, propagate, and die; to be transferred into other membranes; to exchange informative material according to flexible rules; and to mutate and be selected by external agents. This allows the exploration of hierarchical interactive dynamics resulting from the probabilistic interaction of genes (phenotypes), clones, species, hosts, environments, and antibiotic challenges. Our model facilitates analysis of several aspects of the rules that govern the multilevel evolutionary biology of antibiotic resistance. We examined a number of selected landscapes where we predict the effects of different rates of patient flow from hospital to the community and vice versa, the cross-transmission rates between patients with bacterial propagules of different sizes, the proportion of patients treated with antibiotics, and the antibiotics and dosing found in the opening spaces in the microbiota where resistant phenotypes multiply. We also evaluated the selective strengths of some drugs and the influence of the time 0 resistance composition of the species and bacterial clones in the evolution of resistance phenotypes. In summary, we provide case studies analyzing the hierarchical dynamics of antibiotic resistance using a novel computing model with reciprocity within and between levels of biological organization, a type of approach that may be expanded in the multilevel analysis of complex microbial landscapes. ; IMPORTANCE The work that we present here represents the culmination of many years of investigation in looking for a suitable methodology to simulate the multihierarchical processes involved in antibiotic resistance. Everything started with our early appreciation of the different independent but embedded biological units that shape the biology, ecology, and evolution of antibiotic-resistant microorganisms. Genes, plasmids carrying these genes, cells hosting plasmids, populations of cells, microbial communities, and host's populations constitute a complex system where changes in one component might influence the other ones. How would it be possible to simulate such a complexity of antibiotic resistance as it occurs in the real world? Can the process be predicted, at least at the local level? A few years ago, and because of their structural resemblance to biological systems, we realized that membrane computing procedures could provide a suitable frame to approach these questions. Our manuscript describes the first application of this modeling methodology to the field of antibiotic resistance and offers a bunch of examples—just a limited number of them in comparison with the possible ones to illustrate its unprecedented explanatory power. ; This work was supported by the European Commission, Seven Framework Program (EVOTAR; FP7-HEALTH-282004) to F. Baquero, T. Coque, V. Fernandez-Lanza, and M. Campos; the Instituto de Salud Carlos III of Spain (Plan Estatal de IDi 2013-2016, grant PI15-00818 and FIS18-1942; CIBERESP, grant CB06/02/0053, and the EU Joint Programming Initiative JPIAMR2016-AC16/00036 to F. Baquero; the Regional Government of Madrid (InGEMICS-C; S2017/BMD-3691) to T. Coque and F. Baquero; and SAF2015-65878-R (MINECO, Spain) and PrometeoII/2014/065 (Generalitat Valenciana, Spain) to A. Moya (all cofinanced by the European Development Regional Fund [ERDF] "A Way to Achieve Europe"). ; Peer reviewed

In this article, we introduce ARES (Antibiotic Resistance Evolution Simulator) a software device that simulates P-system model scenarios with five types of nested computing membranes oriented to emulate a hierarchy of eco-biological compartments, i.e. a) peripheral ecosystem; b) local environment; c) reservoir of supplies; d) animal host; and e) host's associated bacterial organisms (microbiome). Computational objects emulating molecular entities such as plasmids, antibiotic resistance genes, antimicrobials, and/or other substances can be introduced into this framework and may interact and evolve together with the membranes, according to a set of pre-established rules and specifications. ARES has been implemented as an online server and offers additional tools for storage and model editing and downstream analysis ; This work has also been supported by grants BFU2012-39816-C02-01 (co-financed by FEDER funds and the Ministry of Economy and Competitiveness, Spain) to AL and Prometeo/2009/092 (Ministry of Education, Government of Valencia, Spain) and Explora Ciencia y Explora Tecnologia/SAF2013-49788-EXP (Spanish Ministry of Economy and Competitiveness) to AM. IRF is recipient of a "Sara Borrell" postdoctoral fellowship (Ref. CD12/00492) from the Ministry of Economy and Competitiveness (Spain). We are also grateful to the Spanish Network for the Study of Plasmids and Extrachromosomal Elements (REDEEX) for encouraging and funding cooperation among Spanish microbiologists working on the biology of mobile genetic elements (Spanish Ministry of Science and Innovation, reference number BFU2011-14145-E). ; Campos Frances, M.; Llorens, C.; Sempere Luna, JM.; Futami, R.; Rodríguez, I.; Carrasco, P.; Capilla, R. (2015). A membrane computing simulator of trans-hierarchical antibiotic resistance evolution dynamics in nested ecological compartments (ARES). Biology Direct. 10(41):1-13. https://doi.org/10.1186/s13062-015-0070-9 ; S ; 1 ; 13 ; 10 ; 41 ; Baquero F, Coque TM, Canton R. Counteracting antibiotic resistance: breaking ...

VRE isolates from pigs (n = 29) and healthy persons (n = 12) recovered during wide surveillance studies performed in Portugal, Denmark, Spain, Switzerland, and the United States (1995 to 2008) were compared with outbreak/prevalent VRE clinical strains (n = 190; 23 countries; 1986 to 2009). Thirty clonally related Enterococcus faecium clonal complex 5 (CC5) isolates (17 sequence type 6 [ST6], 6 ST5, 5 ST185, 1 ST147, and 1 ST493) were obtained from feces of swine and healthy humans. This collection included isolates widespread among pigs of European Union (EU) countries since the mid-1990s. Each ST comprised isolates showing similar pulsed-field gel electrophoresis (PFGE) patterns (≤6 bands difference; >82% similarity). Some CC5 PFGE subtype strains from swine were indistinguishable from hospital vancomycin-resistant enterococci (VRE) causing infections. A truncated variant of Tn1546 (encoding resistance to vancomycin) and tcrB (coding for resistance to copper) were consistently located on 150- to 190-kb plasmids (reppLG1). E. faecium CC17 (ST132) isolates from pig manure and two clinical samples showed identical PFGE profiles and contained a 60-kb mosaic plasmid (repInc18 plus reppRUM) carrying diverse Tn1546-IS1216 variants. The only Enterococcus faecalis isolate obtained from pigs (CC2-ST6) corresponded to a multidrug-resistant clone widely disseminated in hospitals in Italy, Portugal, and Spain, and both animal and human isolates harbored an indistinguishable 100-kb mosaic plasmid (reppRE25 plus reppCF10) containing the whole Tn1546 backbone. The results indicate a current intra- and international spread of E. faecium and E. faecalis clones and their plasmids among swine and humans.

The first documented nosocomial outbreak caused by Serratia marcescens in Spain occurred in 1969 at the neonatal intensive care unit (NICU) of the tertiary La Paz Children's Hospital in Madrid, Spain, and based on the available phenotyping techniques at this time, it was considered as a monoclonal outbreak. Only 47 years later, another S. marcescens outbreak of an equivalent dimension occurred at the same NICU. The aim of the present study was to study isolates from these historical and contemporary outbreaks by phenotypic analysis and whole-genome sequencing techniques and to position these strains along with 444 publicly available S. marcescens genomes, separately comparing core genome and accessory genome contents. Clades inferred by both approaches showed high correlation, indicating that core and accessory genomes seem to evolve in the same manner for S. marcescens. Nine S. marcescens clusters were identified, and isolates were grouped in two of them according to sampling year. One exception was isolate 13F-69, the most genetically distant strain, located in a different cluster. Categorical functions in the annotated accessory genes of both collections were preserved among all isolates. No significant differences in frequency of insertion sequences in historical (0.18–0.20)—excluding the outlier strain—versus contemporary isolates (0.11–0.19) were found despite the expected resting effect. The most dissimilar isolate, 13F-69, contains a highly preserved plasmid previously described in Bordetella bronchiseptica. This strain exhibited a few antibiotic resistance genes not resulting in a resistant phenotype, suggesting the value of gene down expression in adaptation to long-term starvation. ; CS was supported by "Fundación Mutua Madrileña" grant to RC achieved in 2017 call with reference number AP165902017. MP-A was supported by the Programa Operativo de Empleo Juvenil, cofinanced by the European Social Fund Investing in your future (ESF) and ERDF (PEJD-2018-PRE/BMD-8237). BP-V was funded by H2020 FTIPilot 2016 project no. 730713 "FAST-bact "A novel fast and automated test for antibiotic susceptibility testing for Gram positive and negative bacteria" and co-funded by Instituto de Salud Carlos III and the European Regional Development Fund (ERDF, "A way to achieve Europe"). FB was supported by grants from the Madrid Regional Government (InGEMICS-C; S2017/BMD-3691) and CIBER (CIBER in Epidemiology and Public Health, CIBERESP; CB06/02/0053), co-funded by Instituto de Salud Carlos III and the European Regional Development Fund (ERDF, "A way to achieve Europe"). This work was supported by the Instituto de Salud Carlos III, PI17/00115 (RC), and REIPI (RD16/0016/0011) actions, cofinanced by the European Development Regional Fund "A way to achieve Europe" (ERDF)

[Background]: Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of "resistomes" (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. [Methods]: We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect "gene abundance" (from 2.0 to 83.2%) and "gene diversity" (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. [Conclusions]: ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role. ; This study was supported by the European Commission, Seven Framework Program (EVOTARFP7-HEALTH-282004 for VFL, FB, JLM, AA, DE, ER, RJLW, WvS, FdlC, and TMC), the Joint Programming Initiative in Antimicrobial Resistance (JPIAMR Third call, STARCS, JPIAMR2016-AC16/00039 to TMC, RJLW, WvS), the Joint Programming Initiative in Water (JPI Water StARE JPIW2013-089-C02-01 to JLM) and the Ministry of Economy and Competitiveness of Spain (BIO2014-54507-R to JLM, and PLASWIRES-612146/FP7-ICT-2013-10 and BFU2014-55534-C2-1-P for FdlC). The authors also acknowledge the European Development Regional Fund "A way to achieve Europe" (ERDF) for co-founding the Spanish R&D National Plan 2012-2019 (BIO2014-54507-R to JLM, PI15-0512 to TMC, PI15-00818 to FB, and BFU2014-55534-C2-1-P to FdlC), CIBER (CIBER in Epidemiology and Public Health, CIBERESP; CB06/02/0053 to FB), the Spanish Network for Research on Infectious Diseases (REIPI RD12/0015 to JLM) and the Regional Government of Madrid (InGeMICS- B2017/BMD-3691). Val F. Lanza was further funded by a Research Award Grant 2016 of the European Society for Clinical Microbiology and Infectious Diseases (ESCMID). Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001 to DE. ; Peer reviewed

BACKGROUND: Antimicrobial resistance is a major global health challenge. Metagenomics allows analyzing the presence and dynamics of "resistomes" (the ensemble of genes encoding antimicrobial resistance in a given microbiome) in disparate microbial ecosystems. However, the low sensitivity and specificity of available metagenomic methods preclude the detection of minority populations (often present below their detection threshold) and/or the identification of allelic variants that differ in the resulting phenotype. Here, we describe a novel strategy that combines targeted metagenomics using last generation in-solution capture platforms, with novel bioinformatics tools to establish a standardized framework that allows both quantitative and qualitative analyses of resistomes. METHODS: We developed ResCap, a targeted sequence capture platform based on SeqCapEZ (NimbleGene) technology, which includes probes for 8667 canonical resistance genes (7963 antibiotic resistance genes and 704 genes conferring resistance to metals or biocides), and 2517 relaxase genes (plasmid markers) and 78,600 genes homologous to the previous identified targets (47,806 for antibiotics and 30,794 for biocides or metals). Its performance was compared with metagenomic shotgun sequencing (MSS) for 17 fecal samples (9 humans, 8 swine). ResCap significantly improves MSS to detect "gene abundance" (from 2.0 to 83.2%) and "gene diversity" (26 versus 14.9 genes unequivocally detected per sample per million of reads; the number of reads unequivocally mapped increasing up to 300-fold by using ResCap), which were calculated using novel bioinformatic tools. ResCap also facilitated the analysis of novel genes potentially involved in the resistance to antibiotics, metals, biocides, or any combination thereof. CONCLUSIONS: ResCap, the first targeted sequence capture, specifically developed to analyze resistomes, greatly enhances the sensitivity and specificity of available metagenomic methods and offers the possibility to analyze genes related to the selection and transfer of antimicrobial resistance (biocides, heavy metals, plasmids). The model opens the possibility to study other complex microbial systems in which minority populations play a relevant role. ; This study was supported by the European Commission, Seven Framework Program (EVOTARFP7-HEALTH-282004 for VFL, FB, JLM, AA, DE, ER, RJLW, WvS, FdlC, and TMC), the Joint Programming Initiative in Antimicrobial Resistance (JPIAMR Third call, STARCS, JPIAMR2016-AC16/00039 to TMC, RJLW, WvS), the Joint Programming Initiative in Water (JPI Water StARE JPIW2013-089-C02-01 to JLM) and the Ministry of Economy and Competitiveness of Spain (BIO2014-54507-R to JLM, and PLASWIRES-612146/FP7-ICT-2013-10 and BFU2014-55534-C2-1-P for FdlC). The authors also acknowledge the European Development Regional Fund "A way to achieve Europe" (ERDF) for co-founding the Spanish R&D National Plan 2012-2019 (BIO2014-54507-R to JLM, PI15-0512 to TMC, PI15-00818 to FB, and BFU2014-55534-C2-1-P to FdlC), CIBER (CIBER in Epidemiology and Public Health, CIBERESP; CB06/02/0053 to FB), the Spanish Network for Research on Infectious Diseases (REIPI RD12/0015 to JLM) and the Regional Government of Madrid (InGeMICSB2017/BMD-3691). Val F. Lanza was further funded by a Research Award Grant 2016 of the European Society for Clinical Microbiology and Infectious Diseases (ESCMID). Additional funding was from the Metagenopolis grant ANR-11-DPBS-0001 to DE.